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#ifndef PCL_FEATURES_IMPL_NORMAL_3D_H_
#define PCL_FEATURES_IMPL_NORMAL_3D_H_

#include "pcl_/normal_estimator.hpp"

namespace iris
{
namespace pcl_
{
///////////////////////////////////////////////////////////////////////////////////////////
template <typename PointInT, typename PointOutT>
void NormalEstimation<PointInT, PointOutT>::computeFeature(PointCloudOut& output)
{
  // Allocate enough space to hold the results
  // \note This resize is irrelevant for a radiusSearch ().
  std::vector<int> nn_indices(k_);
  std::vector<float> nn_dists(k_);

  output.is_dense = true;
  // Save a few cycles by not checking every point for NaN/Inf values if the cloud is set to dense
  if (input_->is_dense) {
    // Iterating over the entire index vector
    for (size_t idx = 0; idx < indices_->size(); ++idx) {
      if (this->searchForNeighbors((*indices_)[idx], search_parameter_, nn_indices, nn_dists) == 0 || !computePointNormal(*surface_, nn_indices, output.points[idx].normal[0], output.points[idx].normal[1], output.points[idx].normal[2], output.points[idx].curvature)) {
        output.points[idx].normal[0] = output.points[idx].normal[1] = output.points[idx].normal[2] = output.points[idx].curvature = std::numeric_limits<float>::quiet_NaN();

        output.is_dense = false;
        continue;
      }

      flipNormalTowardsViewpoint(input_->points[(*indices_)[idx]], vpx_, vpy_, vpz_,
          output.points[idx].normal[0], output.points[idx].normal[1], output.points[idx].normal[2]);
    }
  } else {
    // Iterating over the entire index vector
    for (size_t idx = 0; idx < indices_->size(); ++idx) {
      if (!isFinite((*input_)[(*indices_)[idx]]) || this->searchForNeighbors((*indices_)[idx], search_parameter_, nn_indices, nn_dists) == 0 || !computePointNormal(*surface_, nn_indices, output.points[idx].normal[0], output.points[idx].normal[1], output.points[idx].normal[2], output.points[idx].curvature)) {
        output.points[idx].normal[0] = output.points[idx].normal[1] = output.points[idx].normal[2] = output.points[idx].curvature = std::numeric_limits<float>::quiet_NaN();

        output.is_dense = false;
        continue;
      }

      flipNormalTowardsViewpoint(input_->points[(*indices_)[idx]], vpx_, vpy_, vpz_,
          output.points[idx].normal[0], output.points[idx].normal[1], output.points[idx].normal[2]);
    }
  }
}
template class NormalEstimation<pcl::PointXYZ, pcl::Normal>;

}  // namespace pcl_
}  // namespace iris

#define PCL_INSTANTIATE_NormalEstimation(T, NT) template class PCL_EXPORTS pcl::NormalEstimation<T, NT>;

#endif  // PCL_FEATURES_IMPL_NORMAL_3D_H_